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Published January 2023 | public
Journal Article

A simple force balance model of subduction initiation

Abstract

The initiation and development of subduction zones are associated with substantial stress changes both within plates and at plate boundaries. We formulate a simple analytical model based on the force balance equation of a subduction zone, and validate it with numerical calculations of highly non-linear, coupled thermomechanical system. With two kinds of boundary conditions with either fixed velocity or fixed force in the far-field, we quantitatively analyse the role of each component in the force balance equation, including slab pull, interplate friction, plate bending and basal traction, on the kinematics and stress state of a subducting plate. Based on the numerical and analytical models, we discuss the evolution of plate curvature, the role of plastic yielding and elasticity, and how different factors affect the timing of subduction initiation. We demonstrate with the presence of plastic yielding for a plate of thickness, H, that the bending force is proportional to H², instead of H³ as previously thought. Although elasticity increases the force required to start nucleating subduction it does not substantially change the total work required to initiate a subduction zone when the yielding stress is small. The analytical model provides an excellent fit to the total work and time to initiate subduction and the force and velocity as a function of convergence and time. Plate convergence and weakening rate during nucleation are the dominant factors influencing the force balance of the plate, and 200 km of plate convergence is typically required to bring a nascent subduction zone into a self-sustaining state. The closed-form solution now provides a framework to better interpret even more complex, time-dependent systems in three dimensions.

Additional Information

The authors thank Fabio Capitanio and Ikuko Wada for detailed and insightful reviews which lead to improvements in the manuscript. This work is supported by the National Science Foundation through awards OCE-1654766, EAR-1645775 and OCE-2049086. The authors acknowledge the Texas Advanced Computing Center (TACC) at The University of Texas at Austin for providing HPC resources that have contributed to the research results reported within this paper.

Additional details

Created:
August 22, 2023
Modified:
October 24, 2023